Triple
T18621597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coryell County |
E455163
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Oglesby, Texas |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Oglesby, Texas | Statement: [Coryell County, hasCity, Oglesby, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oglesby, Texas Context triple: [Coryell County, hasCity, Oglesby, Texas]
-
A.
Oglesby, Texas
chosen
Oglesby, Texas is a small rural city in Central Texas known for its tight-knit community and agricultural surroundings.
-
B.
Oglethorpe, Texas
Oglethorpe, Texas is a small unincorporated community in Texas, United States.
-
C.
Goodrich, Texas
Goodrich, Texas is a small rural city in East Texas known for its close-knit community and location near Lake Livingston.
-
D.
Van Alstyne, Texas
Van Alstyne, Texas is a small North Texas city known for its historic downtown, rural charm, and growing role as a bedroom community between Sherman and the Dallas–Fort Worth metroplex.
-
E.
Burleson, Texas
Burleson, Texas is a growing suburban city in the Dallas–Fort Worth metropolitan area known for its family-friendly neighborhoods and proximity to Fort Worth.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54f0146f48190a872032db6e660c6 |
completed | April 19, 2026, 9:54 p.m. |
Created at: April 10, 2026, 11:46 a.m.